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Tenure-Track Assistant or Tenured Associate Professor Faculty Position in Artificial Intelligence and Industrial Experiments

Closes:

48
Appointment Status: Tenure

Department: IU Bloomington Vice Provost For Faculty Affairs

Location
Bloomington

Position Summary
Indiana University Bloomington (IUB) invites applications for one tenure-track assistant or associate professor in the Luddy School of Informatics, Computing, and Engineering in the field of AI and Industrial Experiments. We seek candidates to join IU's outstanding Computing and Engineering research program to lead research in areas such as machine learning, agentic AI, edge AI, physical AI and AI safety. We encourage applications from scholars who apply interdisciplinary perspectives and share important research overlap with current IUB scholars while also offering new dimensions that will expand and strengthen the Luddy School's research program. These 10-month appointments would ideally start August 1, 2027, although an earlier or later start date is negotiable. Applications received by November 1, 2026, will receive full consideration, and applications will be accepted until the positions are filled. Responsibilities: Tenured/tenure-track faculty at Indiana University Bloomington are expected to substantially contribute to the overall academic excellence of their department by developing and/or maintaining a robust research portfolio including pursuing and obtaining major extramural research funding to conduct cutting-edge research both as a corresponding principal investigator and a collaborating investigator; teaching and mentoring undergraduate and/or graduate students as designated by the department chairperson; and actively providing service within the department, school and university alongside active engagement with the profession and/or the community. We invite applications from candidates whose research advances the foundations and frontiers of artificial intelligence and its translation into industrial practice. Candidates with special interest in the following areas are encouraged to apply:
  • machine learning methods underpinning foundation models;
  • agentic AI and AI-based model orchestration;
  • edge AI and resource-constrained deployment;
  • physical and embodied AI, including industrial control, and cyber-physical systems; and trustworthy AI, covering safety, robustness, privacy, and alignment.

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